Multiple endocrine neoplasia-IIb (MEN-IIb) is a rare hereditary autosomal dominant syndrome caused by mutations in the RET proto-oncogene. It's characterized by medullary thyroid carcinoma (MTC), pheochromocytoma (PHEO), mucosal neuromas, and Marfanoid habitus. Because of the rarity of MEN-IIb and finiteness of clinical cognition, the majority of the patients suffer a delayed diagnosis. A MEN-IIb patient with the lingual mucosal neuromas since childhood was admitted in the Third Xiangya Hospital of Central South University in November, 2018. He had surgical history of mitral valve prolapse and spinal deformity. He was diagnosed with MTC and PHEO at the age of 22 and 28, respectively, and received surgical treatments. Sequencing of RET gene revealed a de novo heterozygous p.M918T mutation in the patient. Being aware of the unique clinical phenotype and screening of RET gene mutation may lead to the early diagnosis and better long-term outcome for MEN-IIb.Small cell lung cancer belongs to neuroendocrine tumors and is the most malignant one in lung cancer. It possesses clinical features such as rapid growth, easy early metastasis, and poor prognosis. PET/CT is a molecular imaging technique that combines morphological and metabolic imaging. It has been widely used in the diagnosis, staging, treatment planning, efficacy and prognosis evaluation of tumors. This article reviews the efficacy, prognostic parameters, evaluation criteria, possible influencial factors, clinical application and value of 18F-fluorodeoxyglucose (18F-FDG) PET/CT in small cell lung cancer. The accuracy and sensitivity of 18F-FDG PET/CT in small cell lung cancer stage, efficacy and prognosis evaluation are significantly higher than those of traditional imaging methods. Maximal standardized uptake, metabolic tumor volume, and total lesion glycolysis have been applied in efficacy and prognosis prediction, which have important value in developing the personalized treatment and improving the survival for small cell lung cancer patient.The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a major outbreak in the world. SARS-CoV-2 infection can not only involve in the respiratory system, but also cause severe nervous system damage. Studies have shown that SRAS-CoV-2 can invade the nervous system through hematogenous and transneuronal pathways, and may cause nervous system damage in patients with COVID-19 by inhibiting cellular immunity, hypoxemia, inflammation, inducing neuronal degeneration and apoptosis, and angiotensin converting enzyme 2 (ACE2) mechanism. It can lead to intracranial infection, toxic encephalopathy, acute cerebrovascular disease, muscle damage, peripheral nervous system injury, acute myelitis, demyelination disease or other nervous system diseases.Coronavirus disease 2019 (COVID-19) is now a major public health problem worldwide. Infectivity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is extremely strong. The one major target of the virus is the lung, which leads to the deaths of respiratory distress syndrome and multiple organ failure. The kidney is also one of the main organs attacked by viruses, which directly damage the renal tubules through angiotensin converting enzyme-2 and cause cytokine storm, resulting in kidney damage and increasing the risk of death in the patients. Early investigation of risk factors for kidney injury, detection of kidney injury indicators, timely supporting treatment and renal replacement therapy for the existence of kidney injury patients are useful for reducing the mortality rate of COVID-19 patients.Osteosarcoma is the most common malignant tumors of bone. Since 1970s, researchers had used chemotherapy drugs to treat osteosarcoma. However, multidrug resistance is a major adverse reaction that affects the efficacy of chemotherapy drugs, leading to the reduced survival rate of osteosarcoma patients. The Notch signaling pathway plays an important role in osteosarcoma proliferation, which affects tumor resistance by reducing intracellular drug accumulation, regulating epithelial-mesenchymal transition, dysregulating microRNA, disrupting the expression of apoptosis genes, and regulating tumor stem cells.Depression has a high incidence in patients with cardiovascular diseases (CVD) and shows adverse effects on their life quality and prognosis. With the advent of new antidepressant drugs, oral antidepressant drugs are increasingly used in CVD patients with depression, and their efficacy and safety have attracted attention. Commonly used antidepressant drugs have many adverse reactions. When applying antidepressant drugs in CVD patients, we should pay special attention to their cardiovascular adverse reactions and their interaction drugs with commonly used CVD drugs. Clinicians should comprehensively evaluate and select appropriate antidepressant drugs for patients.Cardiomyocytes injury model has been widely used in the study for the molecular mechanism of cardiovascular diseases and drug action. It is very important to select the appropriate model due to the different formation mechanisms for various models. Clinical cardiovascular pathological change is relatively complex. Currently used models according to the characteristics of clinical cardiovascular diseases mainly include hydrogen peroxide-induced myocardial cell damage model, hypoxia reoxygenation injury model, adriamycin-induced myocardial cell damage model, high sugar high fat-induced myocardial cell damage model, and isoprenaline-induced myocardial cell damage model. Every model has its advantages as well as its disadvantages. https://www.selleckchem.com/products/b022.html The suitable model of myocardial cell injury can be selected according to the research purpose.To explore the application of random forest algorithm in screening the risk factors and predictive values for postpartum depression.
We recruited the participants from a tertiary hospital between June 2017 and June 2018 in Changsha City, and followed up from pregnancy up to 4-6 weeks postpartum.Demographic economics, psychosocial, biological, obstetric, and other factors were assessed at first trimesters with self-designed obstetric information questionnaire and the Chinese version of Edinburgh Postnatal Depression Scale (EPDS). During 4-6 weeks after delivery, the Chinese version of EPDS was used to score depression and self-designed questionnaire to collect data of delivery and postpartum. The data of subjects were randomly divided into the training data set and the verification data set according to the ratio of 3?1. The training data set was used to establish the random forest model of postpartum depression, and the verification data set was used to verify the predictive effects via the accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and AUC index.